English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

level data of GWAS becomes increasingly important in post-GWAS data mining. Here, we present GIGSEA (Genotype Imputed Gene Set Enrichment Analysis), a novel method that uses GWAS summary statistics and eQTL to infer differential gene expression and interrogate gene set enrichment for the trait-associated SNPs. By incorporating empirical eQTL of the disease relevant tissue, GIGSEA naturally accounts for factors such as gene size, gene boundary, SNP distal regulation and multiple-marker regulation. The weighted linear regression model was used to perform the enrichment test, properly adjusting for imputation accuracy, model incompleteness and redundancy in different gene sets. The significance level of enrichment is assessed by the permutation test, where matrix operation was employed to dramatically improve computation speed. GIGSEA has appropriate type I error rates, and discovers the plausible biological findings on the real data set.

GIGSEA: genotype imputed gene set enrichment analysis using GWAS summary level data